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Wong MC, Ng BK, Tian I, Sobhiyeh S, Pagano I, Dechenaud M, Kennedy SF, Liu YE, Kelly NN, Chow D, Garber AK, Maskarinec G, Pujades S, Black MJ, Curless B, Heymsfield SB, Shepherd JA. A pose-independent method for accurate and precise body composition from 3D optical scans. Obesity (Silver Spring) 2021; 29:1835-1847. [PMID: 34549543 PMCID: PMC8570991 DOI: 10.1002/oby.23256] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 06/21/2021] [Accepted: 06/22/2021] [Indexed: 12/12/2022]
Abstract
OBJECTIVE The aim of this study was to investigate whether digitally re-posing three-dimensional optical (3DO) whole-body scans to a standardized pose would improve body composition accuracy and precision regardless of the initial pose. METHODS Healthy adults (n = 540), stratified by sex, BMI, and age, completed whole-body 3DO and dual-energy X-ray absorptiometry (DXA) scans in the Shape Up! Adults study. The 3DO mesh vertices were represented with standardized templates and a low-dimensional space by principal component analysis (stratified by sex). The total sample was split into a training (80%) and test (20%) set for both males and females. Stepwise linear regression was used to build prediction models for body composition and anthropometry outputs using 3DO principal components (PCs). RESULTS The analysis included 472 participants after exclusions. After re-posing, three PCs described 95% of the shape variance in the male and female training sets. 3DO body composition accuracy compared with DXA was as follows: fat mass R2 = 0.91 male, 0.94 female; fat-free mass R2 = 0.95 male, 0.92 female; visceral fat mass R2 = 0.77 male, 0.79 female. CONCLUSIONS Re-posed 3DO body shape PCs produced more accurate and precise body composition models that may be used in clinical or nonclinical settings when DXA is unavailable or when frequent ionizing radiation exposure is unwanted.
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Affiliation(s)
- Michael C Wong
- Graduate Program in Human Nutrition, University of Hawai'i Manoa, Honolulu, Hawaii, USA
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA
| | - Bennett K Ng
- Department of Emerging Growth and Incubation, Intel Corp., Santa Clara, California, USA
| | - Isaac Tian
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington, USA
| | - Sima Sobhiyeh
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Ian Pagano
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA
| | - Marcelline Dechenaud
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Samantha F Kennedy
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA
| | - Yong E Liu
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA
| | - Nisa N Kelly
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA
| | - Dominic Chow
- John A. Burns School of Medicine, University of Hawai'i, Honolulu, Hawaii, USA
| | - Andrea K Garber
- School of Medicine, University of California, San Francisco, California, USA
| | - Gertraud Maskarinec
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA
| | - Sergi Pujades
- Inria, Université Grenoble Alpes, CNRS, Grenoble INP, LJK, Grenoble, France
| | - Michael J Black
- Max Planck Institute for Intelligent Systems, Tübingen, Germany
| | - Brian Curless
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington, USA
| | - Steven B Heymsfield
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana, USA
| | - John A Shepherd
- Graduate Program in Human Nutrition, University of Hawai'i Manoa, Honolulu, Hawaii, USA
- Department of Epidemiology, University of Hawai'i Cancer Center, Honolulu, Hawaii, USA
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Sobhiyeh S, Dunkel A, Dechenaud M, Mehrnezhad A, Kennedy S, Shepherd J, Wolenski P, Heymsfield SB. Digital anthropometric volumes: Toward the development and validation of a universal software. Med Phys 2021; 48:3654-3664. [PMID: 33694162 DOI: 10.1002/mp.14829] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2020] [Revised: 02/23/2021] [Accepted: 02/25/2021] [Indexed: 01/22/2023] Open
Abstract
PURPOSE Anthropometry is a method for quantifying body size and shape often used to derive body composition and health risk prediction models. Recent technology advancements led to development of three-dimensional (3D) optical scanners that can overcome most of the limitations associated with manual anthropometric data collection. However, each of the currently available devices offers proprietary measurements that do not match conventional anthropometric definitions. The aim of the current study was to develop and then evaluate the precision and accuracy of new "universal" 3D optical analysis software that calculates digital anthropometric volumes using identical standard landmarks across scanners. METHODS Dual-energy x-ray absorptiometry (DXA) and air displacement plethysmography (ADP) total body and regional volume and fat mass reference measurements and 3D optical scans from two proprietary devices were collected from 356 participants to evaluate the robustness of total body and regional volume and fat mass measurements calculated by the developed software. Linear regression modeling with threefold cross validation was used to evaluate total body and regional fat masses from 3D scans. RESULTS Total body and regional volumes measured by DXA and ADP had strong associations with corresponding estimates from the commercial 3D optical scanners coupled with the universal software (e.g., R2 = 0.98 for Styku and R2 = 1.00 for SS20, for both DXA and ADP comparisons). Regional body volumes also had strong correlation between DXA and the 3DO scanners (e.g., for arm, leg and trunk, respective R2 s of 0.75, 0.86, and 0.97 for Styku and 0.79, 0.89, and 0.98 for SS20). Similarly, there were strong associations between DXA- measured total body and regional fat mass and 3D optical estimates calculated by the universal software (e.g., for total body, arm, leg and trunk, respective R2 s of 0.86, 0.72, 0.77, and 0.88 for Styku and 0.84, 0.76, 0.78, and 0.85 for SS20). Absolute differences in volumes and fat mass between the reference methods and the universal software values revealed underlying proprietary scanner differences that can be improved when designing future devices. CONCLUSIONS The current study suggests that, when compared against values calculated using DXA and ADP, the universal software was able to measure total and regional body volumes reliably from scans obtained by two different scanners. The universal software, with future refinements, combined with potential optical scanner design improvements, creates new opportunities for developing large multicenter anthropometric databases with uniformly defined body dimensions that can be used for modeling health risks. CLINICAL TRIAL REGISTRATION ID Shape Up! Adults Study, NCT0363785.
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Affiliation(s)
- Sima Sobhiyeh
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | | | | | | | - Samantha Kennedy
- Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - John Shepherd
- University of Hawaii Cancer Center, Honolulu, HI, 9681, USA
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Dechenaud ME, Kennedy S, Sobhiyeh S, Shepherd J, Heymsfield SB. Total body and regional surface area: Quantification with low-cost three-dimensional optical imaging systems. Am J Phys Anthropol 2021; 175:865-875. [PMID: 33543784 DOI: 10.1002/ajpa.24243] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 12/17/2020] [Accepted: 01/19/2021] [Indexed: 01/25/2023]
Abstract
OBJECTIVES Body surface area (SA) is a widely used physical measure incorporated into multiple thermophysiology and evolutionary biology models currently estimated in humans either with empirical prediction equations or costly whole-body laser imaging systems. The introduction of low-cost 3D scanners provides a new opportunity to quantify total body (TB) and regional SA, although a critical question prevails: can these devices acquire the quality of depth information and process this initial data to form a mesh that has the fidelity needed to generate accurate SA estimates? MATERIALS AND METHODS This question was answered by comparing SA estimates calculated using images from four commercial 3D scanners in 108 adults to corresponding estimates acquired with a whole-body laser system. This was accomplished by processing initial mesh data from all devices, including the laser system, with the same universal software adapted specifically for repairing mesh gaps, identifying landmarks, and generating SA measurements. RESULTS TB SA measured on all four 3D scanners was highly correlated with corresponding laser system estimates (R2 s, 0.98-0.99; all p < 0.001) with some small but significant mean differences (-0.19 to 0.06 m2 ); root-mean square errors (RMSEs) were small (0.02-0.03 m2 ); and significant bias was present for one device. Qualitatively similar results (e.g., R2 s, 0.78-0.95; mean Δs, -0.05 to 0.02 m2 ; RMSEs, 0.01-0.03 m2 ) were present for trunk, arm, and leg SA comparisons. DISCUSSION The current study observations demonstrate that low-cost and practical 3D optical scanners are capable of accurately quantifying TB and regional SA, thus opening new opportunities for evaluating human phenotypes and related physiological characteristics.
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Affiliation(s)
- Marcelline E Dechenaud
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, USA.,Louisiana State University, Baton Rouge, Louisiana, USA
| | - Samantha Kennedy
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, USA
| | - Sima Sobhiyeh
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, USA
| | - John Shepherd
- University of Hawaii Cancer Center, Honolulu, Hawaii, USA
| | - Steven B Heymsfield
- Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, Louisiana, USA
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Sobhiyeh S, Kennedy S, Dunkel A, Dechenaud ME, Weston JA, Shepherd J, Wolenski P, Heymsfield SB. Digital anthropometry for body circumference measurements: Toward the development of universal three-dimensional optical system analysis software. Obes Sci Pract 2020; 7:35-44. [PMID: 33680490 PMCID: PMC7909596 DOI: 10.1002/osp4.467] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 09/30/2020] [Accepted: 10/21/2020] [Indexed: 01/07/2023] Open
Abstract
Background/Objective Digital anthropometric (DA) assessments are increasingly being administered with three‐dimensional (3D) optical devices in clinical settings that manage patients with obesity and related metabolic disorders. However, anatomic measurement sites are not standardized across manufacturers, precluding use of published reference values and pooling of data across research centers. Subjects/Methods This study aimed to develop universal 3D analysis software by applying novel programming strategies capable of producing device‐independent DA estimates that agree with conventional anthropometric (CA) measurements made at well‐defined anatomic sites. A series of technical issues related to proprietary methods of 3D geometrical reconstruction and image analysis were addressed in developing major software components. To evaluate software accuracy, comparisons were made to CA circumference measurements made with a flexible tape at eleven standard anatomic sites in up to 35 adults scanned with three different commercial 3D optical devices. Results Overall, group mean CA and DA values across the three systems were in good agreement, with ∼2 cm systematic differences; CA and DA estimates were highly correlated (all p‐values <0.01); root‐mean square errors were low (0.51–3.27 cm); and CA‐DA bias tended to be small, but significant depending on anatomic site and device. Conclusions Availability of this software, with future refinements, has the potential to facilitate clinical applications and creation of large pooled uniform anthropometric databases.
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Affiliation(s)
- Sima Sobhiyeh
- Metabolism-Body-Composition Pennington Biomedical Research Center LSU System Baton Rouge Louisiana USA
| | - Samantha Kennedy
- Metabolism-Body-Composition Pennington Biomedical Research Center LSU System Baton Rouge Louisiana USA
| | - Alexander Dunkel
- Department of Mathematics Louisiana State University Baton Rouge Louisiana USA
| | | | - Jerome A Weston
- Department of Mathematics Louisiana State University Baton Rouge Louisiana USA
| | - John Shepherd
- Cancer Center University of Hawaii Honolulu Hawaii USA
| | - Peter Wolenski
- Department of Mathematics Louisiana State University Baton Rouge Louisiana USA
| | - Steven B Heymsfield
- Metabolism-Body-Composition Pennington Biomedical Research Center LSU System Baton Rouge Louisiana USA
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Sobhiyeh S, Borel N, Dechenaud M, Graham CA, Wong M, Wolenski P, Shepherd J, Heymsfield SB. Fully Automated Pipeline for Body Composition Estimation from 3D Optical Scans using Principal Component Analysis: A Shape Up Study. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2020:1853-1858. [PMID: 33018361 DOI: 10.1109/embc44109.2020.9175211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
The increasing prevalence and adaptability of 3D optical scan (3DO) technology has invoked many recent studies which use 3DO scanning as a convenient and inexpensive means for predicting body composition and health risks. The Shape Up studies seek a device-agnostic solution for body composition estimation based on principal component analysis (PCA). This paper reports a progress made on Shape Up's previous work which served as a criterion analysis for PCA-based body composition and health risk prediction. This study presents proof-of-concept for a novel automated landmark detection step that allows for a fully automated PCA-based approach to body composition estimation that facilitates a practical device-agnostic PCA-based solution to body composition estimation from 3DO scans. Our results show that replacing expensive and time-consuming manual point placement with the proposed automated landmarks will not diminish the quality of body composition estimates allowing for a more practical pipeline that can be used in real-world settings.
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Kennedy S, Hwaung P, Kelly N, Liu YE, Sobhiyeh S, Heo M, Shepherd JA, Heymsfield SB. Optical imaging technology for body size and shape analysis: evaluation of a system designed for personal use. Eur J Clin Nutr 2020; 74:920-929. [PMID: 31551533 PMCID: PMC7089806 DOI: 10.1038/s41430-019-0501-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Revised: 08/15/2019] [Accepted: 08/20/2019] [Indexed: 11/09/2022]
Abstract
BACKGROUND/OBJECTIVES Three-dimensional optical (3DO) imaging systems that rapidly and accurately provide body shape and composition information are increasingly available in research and clinical settings. Recently, relatively low-cost and space efficient 3DO systems with the ability to report and track individual assessments were introduced to the consumer market for home use. This study critically evaluated the first 3DO imaging device intended for personal operation, the Naked Body Scanner (NBS), against reference methods. PARTICIPANTS/METHODS Circumferences at six standardized anatomic sites were measured with a flexible tape in 90 participants ranging in age (5-74 years), ethnicity, and adiposity. Regression analysis and Bland-Altman plots compared these direct measurements and dual-energy X-ray absorptiometry (DXA) %fat estimates to corresponding NBS values. Method precision was analyzed from duplicate anthropometric and NBS measurements in a subgroup of 51 participants. RESULTS The NBS exhibited greater variation in test-retest reliability (CV, 0.4-2.7%) between the six measured anatomic locations when compared with manually measured counterparts (0.2-0.4%). All six device-derived circumferences correlated with flexible tape references (R2s, 0.84-0.97; p < 0.0001). Measurement bias was apparent for three anatomic sites while mean differences were present for five. The NBS's %fat estimates also correlated with DXA results (R2 = 0.73, p < 0.0001) with no significant bias. CONCLUSIONS This system opens a new era of digital home-based assessments that can be incorporated into weight loss or exercise interventions accessible to clinical investigators as well as individual users.
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Affiliation(s)
- Samantha Kennedy
- Pennington Biomedical Research, Louisiana State University, Baton Rouge, LA, USA
| | - Phoenix Hwaung
- Pennington Biomedical Research, Louisiana State University, Baton Rouge, LA, USA
| | - Nisa Kelly
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Yong E Liu
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Sima Sobhiyeh
- Pennington Biomedical Research, Louisiana State University, Baton Rouge, LA, USA
| | - Moonseong Heo
- Department of Public Health Sciences, Clemson University, Clemson, SC, USA
| | | | - Steven B Heymsfield
- Pennington Biomedical Research, Louisiana State University, Baton Rouge, LA, USA.
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Sobhiyeh S, Dechenaud M, Dunkel A, LaBorde M, Kennedy S, Shepherd J, Heymsfield S, Wolenski P. Hole Filling in 3D Scans for Digital Anthropometric Applications. Annu Int Conf IEEE Eng Med Biol Soc 2020; 2019:2752-2757. [PMID: 31946464 DOI: 10.1109/embc.2019.8856713] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Anthropometric measurements have been used to assess an individual's body composition, disease risk, and nutritional status. Three-dimensional (3D) optical devices can rapidly acquire body surface scans in the form of a triangular mesh which can then be used to obtain anthropometric measurements such as body volume, limb lengths, and circumferences; however, the meshes provided by some scanners may include missing data patches known as holes. These need to be repaired in order to obtain correct landmark detection and automatic calculation of anthropometric measurements-especially body volume. In this study, we present ScReAM (Scan Reconstruction for Anthropometric Measurements) which is a fully automated geometrical 3D reconstruction approach to find and fill these holes. We compare ScReAM with Alias and MeshFix which are well-known software used for triangular meshing. Evaluations are derived from a sample size of 47 subjects that were scanned by two different 3D optical scanners. Our results validate the accuracy of ScReAM for reconstructing a mesh for volume calculation.
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